Prenatal ultrasound and postmortem histologic evaluation of tooth germs: an observational, transversal study

Introduction: Hypodontia is the most frequent developmental anomaly of the orofacial complex, and its detection in prenatal ultrasound may indicate the presence of congenital malformations, genetic syndromes and chromosomal abnormalities.To date, only a few studies have evaluated the histological relationship of human tooth germs identified by two-dimensional (2D) ultrasonography. In order to analyze whether two-dimensional ultrasonography of tooth germs may be successfully used for identifying genetic syndromes, prenatal ultrasound images of fetal tooth germs obtained from a Portuguese population sample were compared with histological images obtained from fetal autopsies.Methods: Observational, descriptive, transversal study. The study protocol followed the ethical principles outlined by the Helsinki Declaration and was approved by the Ethics Committee of the School of Dental Medicine, University of Porto (FMDUP, Porto, Portugal) and of the Centro Hospitalar de Vila Nova de Gaia/Espinho (CHVNG/EPE, Porto, Portugal) as well as by the CGC Genetics Embryofetal Pathology Laboratory. Eighty-five fetuses examined by prenatal ultrasound screening from May 2011 to August 2012 had an indication for autopsy following spontaneous fetal death or medical termination of pregnancy. Of the 85 fetuses, 37 (43.5%) were randomly selected for tooth germ evaluation by routine histopathological analysis. Fetuses who were up to 30 weeks of gestation, and whose histological pieces were not representative of all maxillary tooth germs was excluded. Twenty four fetus between the 13th and 30th weeks of gestation fulfilled the parameters to autopsy.Results: Twenty four fetuses were submitted to histological evaluation and were determined the exact number, morphology, and mineralization of their tooth germs. All tooth germs were identifiable with ultrasonography as early as the 13th week of gestation. Of the fetuses autopsied, 41.7% had hypodontia (29.1% maxillary hypodontia and 20.9% mandibular hypodontia).Conclusions: This results indicateinfo:eu-repo/semantics/publishedVersio

NIBBS-Search for Fast and Accurate Prediction of Phenotype-Biased Metabolic Systems

Understanding of genotype-phenotype associations is important not only for furthering our knowledge on internal cellular processes, but also essential for providing the foundation necessary for genetic engineering of microorganisms for industrial use (e.g., production of bioenergy or biofuels). However, genotype-phenotype associations alone do not provide enough information to alter an organism's genome to either suppress or exhibit a phenotype. It is important to look at the phenotype-related genes in the context of the genome-scale network to understand how the genes interact with other genes in the organism. Identification of metabolic subsystems involved in the expression of the phenotype is one way of placing the phenotype-related genes in the context of the entire network. A metabolic system refers to a metabolic network subgraph; nodes are compounds and edges labels are the enzymes that catalyze the reaction. The metabolic subsystem could be part of a single metabolic pathway or span parts of multiple pathways. Arguably, comparative genome-scale metabolic network analysis is a promising strategy to identify these phenotype-related metabolic subsystems. Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotype-expressing organismal networks. We set up experiments with target phenotypes like hydrogen production, TCA expression, and acid-tolerance. We show via extensive literature search that some of the resulting metabolic subsystems are indeed phenotype-related and formulate hypotheses for other systems in terms of their role in phenotype expression. NIBBS is also orders of magnitude faster than MULE, one of the most efficient maximal frequent subgraph mining algorithms that could be adjusted for this problem. Also, the set of phenotype-biased metabolic systems output by NIBBS comes very close to the set of phenotype-biased subgraphs output by an exact maximally-biased subgraph enumeration algorithm ( MBS-Enum ). The code (NIBBS and the module to visualize the identified subsystems) is available at http://freescience.org/cs/NIBBS

Azo Dyes, Their Environmental Effects, and Defining a Strategy for Their Biodegradation and Detoxification

Intenzivan industrijski razvoj popraćen je sve većom kompleksnošću sastava otpadnih voda, što u smislu učinkovite zaštite okoliša i održivog razvoja nalaže potrebu pospješivanja kvalitete postojećih te uvođenjem novih postupaka obrade otpadnih voda, kao iznimno važnog čimbenika u interakciji čovjeka i okoliša. Posebnu znanstveno-tehnološku pozornost zahtijevaju novosintetizirani ksenobiotici, poput azo-boja, koji su u prirodi veoma teško razgradivi. Azo-boje podložne su bioakumulaciji, a zbog alergijskih, kancerogenih, mutagenih i teratogenih svojstava nerijetko su prijetnja zdravlju ljudi i očuvanju okoliša. Primjenu fi zikalnokemijskih metoda za uklanjanje azo-boja iz otpadnih voda često ograničavaju visoke cijene, potrebe za odlaganjem nastalog štetnog mulja ili nastanak toksičnih sastojaka razgradnje. Biotehnološki postupci su, zbog mogućnosti ekonomične provedbe i postizanja potpune biorazgradnje, a time i detoksifi kacije, sve zastupljeniji u obradi svih vrsta otpadnih voda, pa tako i onih koje sadržavaju azo-boje.Intense industrial development has been accompanied by the production of wastewaters of very complex content, which pose a serious hazard to the environment, put at risk sustainable development, and call for new treatment technologies that would more effectively address the issue. One particular challenge in terms of science and technology is how to biodegrade xenobiotics such as azo dyes, which practically do not degrade under natural environmental conditions. These compounds tend to bioaccumulate in the environment, and have allergenic, carcinogenic, mutagenic, and teratogenic properties for humans. Removal of azo dyes from effl uents is mostly based on physical-chemical methods. These methods are often very costly and limited, as they accumulate concentrated sludge, which also poses a significant secondary disposal problem, or produce toxic end-products. Biotechnological approach may offer alternative, lowcost biological treatment systems that can completely biodegrade and detoxify even the hard-to-biodegrade azo dyes

Comparison of white-rot fungi cultures for decolorization of textile dyestuffs

Four different white rot fungi cultures were used for decolorization of five different textile dyestuffs. Phanerochaeta chrysosporium 671.71, P. chrysosporium MUCL, Coriolus versicolor and C, versicolor MUCL cultures effectively decolorized Everzol Yellow 4GL, Everzol Red RBN, D. Orange K-GL, Everdirect Supra yellow PG and Everzol Turquoise Blue G textile dyestuffs in shake flasks within 9 days of incubation period. Decolorization efficiencies obtained with P. chrysosporium were above 90% for all dyestuffs tested. C. versicolor cultures resulted in varying degree of decolorization efficiencies between 34% and 100%